Copertina

Open-Ended Task Discovery via Bayesian Optimization

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Adachi, Masaki, Suzuki, Yuta, Ziomek, Juliusz
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence Machine Learning 62C10, 62F15
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs
di: Adachi, Masaki, et al.
Pubblicazione: (2026)

A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting
di: Adachi, Masaki, et al.
Pubblicazione: (2024)

Fixing the Pitfalls of Probabilistic Time-Series Forecasting Evaluation by Kernel Quadrature
di: Adachi, Masaki, et al.
Pubblicazione: (2025)

Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach
di: Adachi, Masaki, et al.
Pubblicazione: (2023)

Looping in the Human Collaborative and Explainable Bayesian Optimization
di: Adachi, Masaki, et al.
Pubblicazione: (2023)

Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature
di: Adachi, Masaki, et al.
Pubblicazione: (2022)

Bayesian Optimization for Building Social-Influence-Free Consensus
di: Adachi, Masaki, et al.
Pubblicazione: (2025)

Minimaxity and Admissibility of Bayesian Neural Networks
di: Coulson, Daniel Andrew, et al.
Pubblicazione: (2026)

Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation
di: Rosa, Rafael Mouallem, et al.
Pubblicazione: (2026)

Variational Sequential Optimal Experimental Design using Reinforcement Learning
di: Shen, Wanggang, et al.
Pubblicazione: (2023)

Bayesian--AI Fusion for Epidemiological Decision Making: Calibrated Risk, Honest Uncertainty, and Hyperparameter Intelligence
di: Chatterjee, Debashis
Pubblicazione: (2025)

Optimizing Data Augmentation through Bayesian Model Selection
di: Matymov, Madi, et al.
Pubblicazione: (2025)

Consistent DAG selection for Bayesian causal discovery under general error distributions
di: Chaudhuri, Anamitra, et al.
Pubblicazione: (2025)

Consistent Bayesian causal discovery for structural equation models with equal error variances
di: Chaudhuri, Anamitra, et al.
Pubblicazione: (2025)

Universal Adaptive Environment Discovery
di: Matymov, Madi, et al.
Pubblicazione: (2025)

Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning
di: Shen, Wanggang, et al.
Pubblicazione: (2021)

Bayesian taut splines for estimating the number of modes
di: Chacón, José E., et al.
Pubblicazione: (2023)

Variational Inference for Latent Variable Models in High Dimensions
di: Zhong, Chenyang, et al.
Pubblicazione: (2025)

Response to: "A note on conditional densities, Bayes' rule, and recent criticisms of Bayesian inference" by Yan et al., 2026
di: Mosegaard, Klaus, et al.
Pubblicazione: (2026)

A comparison between initialization strategies for the infinite hidden Markov model
di: Cortese, Federico P., et al.
Pubblicazione: (2025)

A2 Copula-Driven Spatial Bayesian Neural Network For Modeling Non-Gaussian Dependence: A Simulation Study
di: Aich, Agnideep, et al.
Pubblicazione: (2025)

Hierarchical inference of evidence using posterior samples
di: Rinaldi, Stefano, et al.
Pubblicazione: (2024)

Bayesian prediction regions and density estimation with type-2 censored data
di: Asgharzadeh, Akbar, et al.
Pubblicazione: (2024)

Order selection in GARMA models for count time series: a Bayesian perspective
di: Lastra, Katerine Zuniga, et al.
Pubblicazione: (2024)

On Bayesian Softmax-Gated Mixture-of-Experts Models
di: Bariletto, Nicola, et al.
Pubblicazione: (2026)

Upper and lower bounds for local Lipschitz stability of Bayesian posteriors
di: Cvetković, Nada, et al.
Pubblicazione: (2025)

Complex-Valued Signal Recovery using the Bayesian LASSO
di: Green, Dylan, et al.
Pubblicazione: (2024)

Bayesian Inference for Left-Truncated Log-Logistic Distributions for Time-to-event Data Analysis
di: Mostafa, Fahad, et al.
Pubblicazione: (2025)

Bayesian Joint Additive Factor Models for Multiview Learning
di: Anceschi, Niccolo, et al.
Pubblicazione: (2024)

Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems
di: Gruhlke, Robert, et al.
Pubblicazione: (2025)

Uncertainty Quantification Via the Posterior Predictive Variance
di: Chaudhuri, Sanjay, et al.
Pubblicazione: (2026)

Pair-based estimators of infection and removal rates for stochastic epidemic models
di: Temple, Seth D., et al.
Pubblicazione: (2026)

Variational Bayesian Optimal Experimental Design with Normalizing Flows
di: Dong, Jiayuan, et al.
Pubblicazione: (2024)

Decision synthesis in monetary policy
di: Chernis, Tony, et al.
Pubblicazione: (2024)

Bayesian inference on the order of stationary vector autoregressions
di: Binks, Rachel L., et al.
Pubblicazione: (2023)

Designing truncated priors for direct and inverse Bayesian problems
di: Agapiou, Sergios, et al.
Pubblicazione: (2021)

Upper Bound of Bayesian Generalization Error in Partial Concept Bottleneck Model (CBM): Partial CBM outperforms naive CBM
di: Hayashi, Naoki, et al.
Pubblicazione: (2024)

Bayesian experimental design: grouped geometric pooled posterior via ensemble Kalman methods
di: Yang, Huchen, et al.
Pubblicazione: (2026)

Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference
di: Wang, Zheyu Oliver, et al.
Pubblicazione: (2023)

Semiparametric Uncertainty Quantification via Isotonized Posterior for Deconvolutions
di: Gili, Francesco, et al.
Pubblicazione: (2026)